Name
Abstract | ||
|---|---|---|
Moving cast shadow detection is an essential and pivotal problem in image processing. One problem is that many existed moving cast shadow detection methods are only suitable for some specific situations. In order to solve this problem, a cast shadow detection and elimination algorithm based on the combination of texture feature and YUV color space is proposed in this paper. Firstly, we detect moving object using PBAS algorithm which suppress ghost region. Furthermore, a part of cast shadow candidate region is obtained by texture detection. Then, the other cast shadow candidate region is obtained by shadow detection based on YUV color space. Finally, two parts of the cast shadow candidate regions are screened and merged by the shadow feature. Experimental results show that the proposed method has higher detection rates and discrimination rates compared to some well-known methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-92537-0_70 | ADVANCES IN NEURAL NETWORKS - ISNN 2018 |
Keywords | Field | DocType |
Cast shadow,Color space,Moving object detection,Texture detection | Shadow,Color space,Pattern recognition,Computer science,Image processing,Artificial intelligence | Conference |
Volume | ISSN | Citations |
10878 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Zheng | 1 | 16 | 6.74 |
| Zhan-Li Sun | 2 | 10 | 4.51 |
| Nan Wang | 3 | 93 | 27.47 |
| Xin-Yuan Bao | 4 | 0 | 0.68 |